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Wolkowitz, Amanda A.; Foley, Brett; Zurn, Jared – Practical Assessment, Research & Evaluation, 2023
The purpose of this study is to introduce a method for converting scored 4-option multiple-choice (MC) items into scored 3-option MC items without re-pretesting the 3-option MC items. This study describes a six-step process for achieving this goal. Data from a professional credentialing exam was used in this study and the method was applied to 24…
Descriptors: Multiple Choice Tests, Test Items, Accuracy, Test Format
Yanagiura, Takeshi – Community College Research Center, Teachers College, Columbia University, 2020
Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…
Descriptors: Community Colleges, Man Machine Systems, Artificial Intelligence, Prediction
Yanagiura, Takeshi – Community College Review, 2023
Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…
Descriptors: Community Colleges, Community College Students, Educational Indicators, Outcomes of Education